C1 Reading Test – The Attention Economy & Cognitive Overload
Explore how platforms compete for attention. C1 multiple-choice questions on cause–effect, inference, and nuanced detail.
Read the passage and decide if each statement is True (T), False (F), or Not Given (NG).
Platforms in the attention economy do not merely host content; they compete to orchestrate when and how long users look. Product teams optimize “time-on-task” using levers such as variable notifications, infinite scroll, and autoplay. These features are defensible as convenience—no friction, instant access—but they also exploit well-known biases: intermittent rewards make checking habitual, and “just one more” removes natural stopping points.
Cognitive overload arises when the number of incoming cues exceeds our capacity to prioritize them. Contrary to popular myth, humans are not efficient multitaskers; most switch rapidly between tasks, paying a penalty each time attention is reoriented. The cost is subtle: memory of the previous context decays while the next task is still being parsed, so quality drops even when total minutes online rise. Over time, this fragmentation can feel like productivity, because dashboards count activity, not depth.
Designers are not villains by default. Many products provide real benefits—navigation, translation, social connection—and the same tools that capture attention can be repurposed to protect it. Batch notifications, default do-not-disturb windows, and session goals introduce boundaries without outlawing engagement. Yet incentives matter. If revenue is tied to minutes watched rather than outcomes achieved, teams face pressure to favor stickiness over clarity.
Regulation tries to catch up. Proposals range from transparency reports on recommendation systems to age-sensitive defaults and limits on “dark patterns.” But precision is hard: defining which nudge informs and which manipulates depends on purpose, reversibility, and the availability of a genuine opt-out. A parallel path focuses on literacy—teaching users to read interface cues the way we once taught advertising analysis—so individuals can recognize when a design is guiding them more than they intended.
Ultimately, overload is not a single mistake but a systems problem: metrics, markets, and habits amplify one another. The practical test is whether products help users align time spent with goals chosen. Where goals are vague, even honest design will drift toward compulsion; where goals are explicit and settings honor them by default, the same technology can scaffold attention rather than siphon it.
Variable notifications and infinite scroll are used to increase time-on-task.
The passage claims humans are efficient multitaskers when well trained.
According to the text, rapid task switching imposes an attentional penalty.
Dashboards typically measure depth of thinking rather than activity.
The author states that designers are primarily to blame for cognitive overload.
Batch notifications and session goals are presented as examples of protective design.
Revenue models tied to minutes watched can encourage stickiness over clarity.
The passage provides a legal definition of “dark patterns” used worldwide.
One regulatory idea mentioned is publishing transparency reports on recommendation systems.
The text concludes that technology inevitably siphons attention regardless of user goals.